Data & BI Engineer — Commodity Markets Analytics (CTRM Platform)
Role Overview
An engineer owning the data and BI layer of our CTRM platform end to end: getting market and trading data in, modelling it, keeping it correct, and putting it in front of traders, analysts and management in a form they use every day.
You work directly with traders, operations, the commercial team, the senior data scientist and the founders — no account manager in between.
Much of the platform is still being built, so you will make real architecture and tooling decisions rather than inherit them.
Some sources are already in the data lake; many are not — a meaningful part of the work starts with vendor APIs, raw exports and spreadsheets someone has maintained by hand for years.
What the work looks like
The platform we are building exists so that anyone involved in a deal can see prices, flows, positions and margin across the chain, at any moment, on agreed and versioned definitions.
Your part is the data underneath that and the decision-support layer on top: market intelligence from third-party providers joined to our own trading and operations data, across crude oil and refined products.
A dashboard here is only as good as the number behind it.
Traders act on spreads and margins within minutes; if a price series is stale, a unit is wrong or a cargo is counted twice, someone loses money before anyone notices.
Key Skills for This Role
Full Job Posting
Requirements
- 4+ years as a Data Engineer, BI Developer, Analytics Engineer or in a comparable role, with ownership of production pipelines and reporting
- Strong SQL; Python for pipelines, automation and analysis (pandas, SQLAlchemy or similar)
- Data modelling in practice — dimensional modelling, star schemas, dbt or equivalent
- Hands-on experience with a BI tool such as Power BI, Tableau, Metabase or Superset, taken from requirement to a dashboard people rely on
- Commodity markets experience, ideally crude oil and refined products. You know what a price assessment, a forward curve, a crack spread and a cargo nomination are, and why the same cargo can appear differently in two data sources. Strong, demonstrable interest can partly compensate; zero exposure will not
- Working with coding agents, seriously. Agents write most of the code here. Bad agent output in data pipelines fails silently: a join fans out rows, a timezone shift moves a price to the wrong day, a unit conversion is applied twice. We hire for verification habits, not speed — row-count and freshness checks, reconciliation against a number someone already trusts, tests on the transformations that matter
- Comfortable working directly with traders and commercial staff, and explaining a data issue in their terms
- English sufficient to present work and defend design decisions
- Professional proficiency in Russian
Nice to have
- Hands-on experience with market data providers (Kpler, Platts, OPIS, Argus, Bloomberg) and their APIs
- Cloud data warehouses (Snowflake, BigQuery, Databricks or similar)
- Workflow orchestration (Airflow, Prefect, Dagster or similar)
- Experience in an energy trading company, commodity house or data-heavy financial environment; exposure to CTRM/ETRM systems
About Raw Ventures
Private UK venture capital firm backing early-stage startups with evergreen capital, AI advisory, and talent-development programs.
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